Cyber Threat Detection Using Machine Learning: A Performance Evaluation Approach
Levina Tukaram · International Journal for Research in Applied Science and Engineering Technology · 2025
Now a day world has come all dependent on cyberspace for every aspect of daily living. The use of cyberspace is increasing with each day by day. The world is spending most of the time on the Internet than ever ahead. As a result, the pitfalls of cyber pitfalls and cybercrimes are increasing day by day. The term' cyber trouble' is applicable to as the illegal exertion performed using the Internet. Cybercriminals are changing their ways with time to pass through the wall of protection. Conventional ways are not able of detecting zero- day attacks and sophisticated attacks. There fore, far, stacks of machine literacy ways have been developed to descry the cybercrimes and battle against cyber pitfalls. The ideal of this exploration work is to present the evaluation of some of the extensively used machine literacy ways used to descry some of the most threatening cyber pitfalls to the cyberspace. Three primary machine literacy ways are substantially delved, including deep belief network, decision tree and support vector machine. We’ve presented a brief disquisition to gauge the performance of these machine literacy ways in the spam discovery, intrusion discovery and malware discovery grounded on constantly used and standard datasets.